Spare Parts Consumption Research Articles

OPTIMIZATION OF THE PROCESSES OF PRODUCTION OF SPARE PARTS FOR MOTOR VEHICLES

The purpose of the research is to develop a software simulation multi-product model designed for effective inventory management of spare parts. In the course of the work, a mathematical model was used to optimize the production and storage of spare parts for vehicles. At the same time, such significant factors as the total number of spare parts in stock, the frequency of failure of certain parts, operating conditions, the intensity of their use, as well as the influence of the human factor were taken into account. The results show that penalties for shipping and dynamic spare parts consumption significantly affect the cost function, while penalties for missing necessary parts significantly affect the minimum inventory level. The results can be applied to the management of spare parts stocks at authorized service centers. The study concludes that seasonal fluctuations in demand for spare parts can be eliminated by creating a scientifically sound spare parts inventory management system.

ВЛИЯНИЕ НАДЕЖНОСТИ АВТОМОБИЛЕЙ НА ЗАТРАТЫ НА ПРИОБРЕТЕНИЕ ЗАПАСНЫХ ЧАСТЕЙ

The operation of road transport is associated with maintaining the serviceability of vehicles. Companies that operate vehicles have different approaches to ensuring their serviceability. Small ones, as a rule, carry out maintenance and repair of vehicles at service stations, while large and medium-sized companies provide conditions for carrying out technical service at their own base. In this case, they are faced with the need to stock with spare parts. It was found that the costs of spare parts account for up to 45 % of all operating costs, their reduction is possible with the correct approach to planning and organization of spare parts supply. This confirms the relevance of the research. As the main factor affecting the cost of spare parts purchasing, the authors proposed to consider the reliability of car units and assemblies. A regularity was established: the reliability of a vehicle decreases with the increase of its service life, while the need for spare parts and, consequently, the purchasing cost of spare parts increases. Spare parts stocks are planned in two groups – for maintenance and repairs. It is possible to plan the consumption of spare parts for maintenance based on the vehicle fleet and on the recommendations of the manufacturer, which regulates the frequency of replacement and the list of spare parts. It is advisable to plan the nomenclature of spare parts for current repairs based on vehicles reliability. Forecasting of spare parts stock based on reliability will allow to manage spare parts stock effectively, to minimize their shelf life and to avoid the purchase of unclaimed spare parts.

Analysis of Failure States of Functional Systems of Aircraft Such as Boeing 737 in the Airline

Abstract The article presents the results of analysis of failures of the main functional systems units of aircraft Boeing 737 during the last 10 years of its operation in the national airline of Latvia ‘Air Baltic Corporation’. Total flight time was T∑ = 322,529 h and 184,538 cycles [1]. These data were obtained from daily reports of defects and unplanned consumption of spare parts for these systems. Failures of instrumental equipment of avionic systems were investigated in detail. Based on calculations of their failure probability and component replacement frequency, a comprehensive system including measures and their technical and instrumental support has been developed to improve maintenance productivity. Such a system requires relatively inexpensive components, is simple and can be used in the operation of this type of aircraft.

Development of a monitoring system for technological equipment of a meat processing plant

Relevance. In the production of meat products and semi-finished products, equipment from the 1990s is often used. Such equipment is not equipped with modern means of transmitting diagnostic data and information about the current status via wireless communication, and requires periodic monitoring during the work shift. Lack of timely diagnostic data can lead to equipment failures and unexpected downtime. At the same time, the development of technical means of communication makes it possible to connect industrial equipment to the Internet and remotely receive data on the current state of the equipment online.Methods. The objects of the study were the MULTIVAC R5200 vacuum thermoforming packaging machine and thermal chambers with installed controllers Aditec MIC 2410, Aditec TP 1000, MIKSTER MCC 2100. Methods of object-oriented programming in Python 3.4.4 were used for the monitoring system under study. For network interaction of technological equipment with cloud services, the MQTT-v3.1.1 data transfer protocol was used.Results. The use of a monitoring system based on the industrial Internet of Things platform made it possible: when packing boiled and smoked sausages, to reduce the maintenance time of the packaging machine and the consumption of spare parts, to reduce the production of low-quality products; when carrying out technological processes in thermal chambers, to completely eliminate spoilage of semi-finished products, to improve the quality of the finished product. In the future, the spread of such technology to the equipment of the entire enterprise will make it possible to solve the problems of collecting a large amount of data on the current state of the equipment, conducting analysis and making managerial decisions.

An empirical study of learning‐to‐rank for spare parts consumption in the repair process

AbstractThe repair process of devices is an important part of the business of many original equipment manufacturers. The consumption of spare parts, during the repair process, is driven by the defects found during inspection of the devices, and these parts are a big part of the costs in the repair process. In previous work, we proposed a data‐driven method for Supply Chain Control Tower solutions to provide support for the automatic check of spare parts consumption in the repair process. In this article, we continue our investigation of a multi‐label classification problem and explore alternatives in the learning‐to‐rank approach, where we simulate the passage of time using more data while training and comparing hundreds of Machine Learning models to provide an automatic check in the consumption of spare parts. We investigate the effects of different train set sizes, retraining intervals, models and hyper‐parameter search using Bayesian Optimization. We define a custom metric, the Ratio of Marked Parts, measuring how many spare parts are marked for revision at the end of the repair process. The results show that we were able to improve the trained models and achieve a higher mean NDCG@20 score of 86% when ranking the expected parts. While focusing on the most recent data, we achieved a NDCG@20 score of 90% and obtained a Ratio of Marked Parts of just 4% of the consumed parts for use in alert generation.

A method for estimating the consumption of spare parts in electromechanical equipment considering maintenance time

A method for estimating the consumption of spare parts in electromechanical equipment considering maintenance time

Joint optimization of bi‐level imperfect maintenance and spare parts inventory considering order quantity

AbstractThe joint optimization of various maintenance actions and the supply of spare parts has received extensive attention in recent years owing to its advantage in reducing the overall operational costs of industrial systems. In this study, a joint optimization model is proposed considering bi‐level imperfect preventive maintenance and spare part ordering. A virtual age reduction model that considers bi‐level imperfect preventive maintenance (PM) is established. Upon each system shutdown, the PM level is determined based on the cost‐effectiveness ratio. Furthermore, an improved (s, S) inventory policy is proposed utilizing the information of the remaining number of PM and accumulated consumption of spare parts. Finally, the joint optimization models consisting of different PM policies and spare parts inventory policies are solved. Case studies show that compared with the traditional (s, S) inventory policy, the proposed joint optimization model can coordinate the ordering quantity of spare parts with the PM policy, and reduce the expected maintenance cost. A sensitivity analysis of the cost parameters is performed to explore their impact on the maintenance economy.

Improvement of the Method of Wear Control of Motor Vehicles and Their Main Units

In the Provisions [1] specific norms of spare parts consumption by mileage intervals before overhaul are given,which created the prerequisites for the management of vehicle wear, which requires a machine-by-machine accounting of spare parts consumption. Analysis of experience in applying these standards revealed their effectiveness from the standpoint of wear management of road transport rolling stock. In this regard, there is a task to further improve the method of rationing and extend it to the main units. In this paper, we propose a method of controlling the wear and tear of the main units on the example of the motor vehicle engine, which provides standards for the cost of current repairs – spare parts and labor costs, as well as the cost of damage due to wear and tear. Based on the information revealed, the average rate of iron in the engine oil for each of the engines under control is calculated, and then determined the average rate of iron in the engine oil, which allowed to determine the dependence of cylinder liner wear on the operating time, oil burnout on wear. As a result of processing the initial information of the under-control vehicle operation, the numerical values of the parameters of the curves of dependences of the cost of current repairs on the operating time, and according to the results of spectral analysis of engine oil and accounting for its refill – engine cylinder wear on the operating time and the cost of compensation for losses from wear were determined

МЕТОДОЛОГИЯ ОПРЕДЕЛЕНИЯ ОПТИМАЛЬНОЙ ПЕРИОДИЧНОСТИ ПРОФИЛАКТИКИ СМАЗОЧНОЙ СИСТЕМЫ АВТОТРАКТОРНОГО ДИЗЕЛЯ

The reliability of automotive engines is an important problem for the country's economy. Wear, and subsequently failures, often cause a rather long downtime of equipment, significant consumption of spare parts, complicate the operation of the machine and tractor fleet. The cost of overhaul of an automotive engine is more than half the amount of the cost of a new one, and the resource after repair is no more than half the resource of a new engine. Over the entire service life of automotive engines, 5-6 times more money is spent on ensuring their operability than on manufacturing. The main operations for the prevention of the lubrication system of a diesel engine are the replacement and refilling of engine oil, on which the engine resource largely depends. Therefore, the volume of refilling and the frequency of oil change determine the efficiency of the engine and are optimization parameters. The function of these factors is the total unit costs of prevention and repair. Minimizing these costs is the essence of the technical and economic method. The paper presents the results of operational studies related to the dependence of refilling parameters, engine oil aging and the failure rate of internal combustion engines. The data on the performance of a diesel engine with and without an oil level regulator are given. According to the results of the work, an adequate mathematical model was obtained with physical variables of the dependence of costs on the frequency of oil change and the volume of one-time topping. The substantiation of the kinetics of the pre-failure state of the main elements of a forced diesel engine during the aging of engine oil was made and the optimal values of preventive parameters were determined.

Development of a model of the technical condition of the engine according to the data of operational observations

The article considers an approach to the use of in-place methods and diagnostic tools in the practice of operating power plants of marine transport vessels, which allow maintenance of engines on demand, depending on their technical condition. It has been determined that under operating conditions it is necessary to know the quantitative values of the wear of the main engine parts and the level of formation of soot and deposits on them without disassembling the engine using indirect diagnostic parameters. For this, a conditional reference model of the actual change in its technical condition has been developed, obtained from the data of operational observations, in the form of quantitative values of wear of parts from their operating time. The model included information about the intensity of carbon deposits in the engine cylinder, which can be used to judge the thickness or amount of carbon deposits formed at a given moment, without disassembling the engine; information about the permissible possibilities and terms of engine operation at the rate of carbon formation established by the model. The raw materials were obtained during the cleaning of the engine cylinders, in which the methods for measuring wear of parts and evaluating carbon deposits were slightly expanded compared to conventional measurement methods. The presence of such a model, which characterizes the change in the technical condition of the engine as it is developed in the form of quantitative characteristics of the wear of its parts and quantitative characteristics of carbon formation, reflecting close to real changes occurring in the engine, makes it possible to expand the information content of in-place diagnostics, increase the controllability of engine reliability; will optimize the timing and frequency of maintenance, more accurately predict the consumption of spare parts and regulate the frequency of maintenance.

МЕТОДИКА ВЫБОРА ВАРИАНТА ТЮНИНГА СМАЗОЧНОЙ СИСТЕМЫ ДВИГАТЕЛЯ

Improving the reliability of automotive engines is an important problem for the country's economy. Engine failures, due to wear, cause significant consumption of spare parts, complicate the operation of machines. The cost of overhaul of automotive engines is 70-80% of their cost, and the secondary resource is 30-40%. Over the entire service life of automotive engines, 5-6 times more money is spent on ensuring their operability than on manufacturing. Therefore, increasing the resource of automotive engines by improving lubrication processes is an urgent problem. One of the effective methods of ensuring the operability of machines is functional tuning. The paper defines it and shows the place of tuning in the system of ensuring the reliability of machines. The method of choosing the option of tuning the engine lubrication system is substantiated. The technique has been tested on specific variants: visual indicator, electronic indicator, hydraulic accumulator, oil pumping system, autonomous lubrication of TKR, oil level regulator, limit automatic. Based on the cost indicators of these options and the values of the relative increase in engine life that they provide, a methodology for choosing the best option for tuning the lubrication system has been developed.

АНАЛИЗ ВЛИЯНИЯ УСЛОВИЙ РАБОТЫ ЛЕСОВОЗНЫХ АВТОПОЕЗДОВ НА НАДЕЖНОСТЬ И СВОЕВРЕМЕННОСТЬ ИХ ТЕХНИЧЕСКОГО ОБСЛУЖИВАНИЯ

The description of the road and natural-climatic conditions for the operation of timber-carrying road trains is given. The main features of logging roads, which are characterized by insufficient infrastructure, are considered. The analysis of the negative consequences of the movement of logging road trains along such logging roads in various natural and climatic conditions is carried out. The dependences of the change in the speed of movement and fuel consumption of a logging road train on the nature of the longitudinal profile of the logging road, the performance of the road train on the distance of hauling timber are given. The patterns of change in the speed of movement and the travel fuel consumption of a logging road train depending on its workload and movement along logging roads with different slope values, as well as road roughness parameters, are analyzed. The influence of road conditions of operation of timber road trains on the reliability of their main units and systems is described. The features of maintenance of timber road trains involved in the process of hauling timber are analyzed. The dependences of the change in the flow of spare parts consumption for maintaining the working condition of cars during the year are considered. The patterns of change with increasing mileage of the KAMAZ-53105 vehicle in the mean time between failures and the coefficient of technical readiness are shown.

СОВЕРШЕНСТВОВАНИЕ МЕТОДОВ РЕЗЕРВИРОВАНИЯ ЗАПАСНЫХ ЧАСТЕЙ ДЛЯ СЕЛЬСКОХОЗЯЙСТВЕННОЙ ТЕХНИКИ НА ОСНОВЕ ГЕНЕТИЧЕСКИХ АЛГОРИТМОВ

The uninterrupted use of agricultural machinery performing fi eld operations is ensured by maintaining their working condition through timely maintenance and prompt elimination of operational failures. The period of inoperative state of machines can be reduced if there is a certain inventory stock of spare parts in the warehouse of the operating company. When determining the stock, taking into account the feasibility of the reservation and the calculation of the required number of the reserved parts, the methods of artifi cial intelligence are to be suffi ciently studied. To justify the method of reserving spare parts for agricultural machinery and determine the eff ect of its industrial implementation, the authors developed a genetic algorithm and software. The developed reservation method was tested at an agricultural enterprise to determine seasonal reserves of spare parts for Don-1500B and TORUM combine harvesters. The designers of the information data model took into account the cost and quantity of consumed spare parts by year, the number of machines consuming spare parts in a particular work season, the time values for installing spare parts on a machine, etc. The use of the genetic algorithm made it possible to identify sixty-six of the most signifi cant items out of 2,500 spare parts that need to be reserved for the harvesting season. It has been established that the method of reserving spare parts for agricultural machinery based on the use of the genetic algorithm in combination with a database containing information on the actual consumption of spare parts by machines for at least three previous years, can reduce the idle time of combines waiting for the delivery of spare parts by 37%, increase the daily productivity of combines by 11.4%, and increase the coeffi cient of the operational availability of combines by 4.38%.

Assessment of individual indicators of tractor reliability in the course of transport operations

The paper presents the results of a study of reliability indicators of wheeled tractors. The assessment of reliability indicators was carried out on the basis of the consumption of spare parts during both scheduled current repairs and maintenance, which are preventive measures, and when eliminating sudden failures that occurred during the operation. The study revealed a significant difference in the reliability of both individual tractors and their systems. Along with this, an analysis of the relationship between the funds for preventive maintenance and the subsequent trouble-free operating time was carried out. These dependencies are also individual.

Optimization of after-sales services with spare parts consumption and repairman travel

This paper studies the optimization of discretionary after-sales services with spare parts consumption and repairman travel. Discretionary service means that the service quality and spare parts consumption are determined by the service provider. We assume that a long service time enables the service provider to perform a thorough repair, which leads to a high repair quality and low spare parts consumption. Each service encounter comprises both repairman travel and repair service steps. We find that the dual concerns of service quality and spare parts consumption lead to a counterintuitive impact of the spare parts price: the service provider would decrease the consumption of spare parts even if selling the spare parts becomes more profitable. In addition, we show that the repairman travelling time has different impacts on the optimal service time given the maximum sojourn time constraint. In particular, as the repairman travelling time increases, the service provider increases the repair time to keep the repair quality at a high level if no sojourn time is guaranteed; however, if a maximum sojourn time is guaranteed, the service provider decreases the repair time to meet the promise.

Research of problems of technical operation of agricultural machines

Tracking devices are increasingly used in automatic control systems for mobile agricultural machines. Many elements are regulated by standards and specifications, and it is of scientific and practical interest to establish a correspondence between the reliability of restored parts and connections with the reliability of machines. This is due to many reasons, one of which is a decrease in the technical potential of the village: the composition of the machine and tractor fleet is decreasing, the physical and moral wear of equipment is progressing. Repair and maintenance of cars due to the price arbitrariness of intermediary structures, mainly on the part of collective farms and farms. For this reason, the reliability and reliability of the machine park of rural producers remain low, negatively affects the agrotechnical timing of mechanized work, their cost. In accordance with the standard technology, standards of labor costs for the repair of machines, standards for the consumption of materials needed for repair, and standards for the consumption of spare parts were created. The economic feasibility of restoring parts is usually assessed by comparing the cost of a new part and the cost of repairing a worn one.

Research on maintenance spare parts requirement prediction based on LSTM recurrent neural network

Abstract The aim of this study was to improve the low accuracy of equipment spare parts requirement predicting, which affects the quality and efficiency of maintenance support, based on the summary and analysis of the existing spare parts requirement predicting research. This article introduces the current latest popular long short-term memory (LSTM) algorithm which has the best effect on time series data processing to equipment spare parts requirement predicting, according to the time series characteristics of spare parts consumption data. A method for predicting the requirement for maintenance spare parts based on the LSTM recurrent neural network is proposed, and the network structure is designed in detail, the realization of network training and network prediction is given. The advantages of particle swarm algorithm are introduced to optimize the network parameters, and actual data of three types of equipment spare parts consumption are used for experiments. The performance comparison of predictive models such as BP neural network, generalized regression neural network, wavelet neural network, and squeeze-and-excitation network prove that the new method is effective and provides an effective method for scientifically predicting the requirement for maintenance spare parts and improving the quality of equipment maintenance.

An optimal combination prediction method of turnover spare parts consumption based on certain weight

Aimed at the situation that the first, second and third exponential smoothing method and the three and four term moving average method are used to forecast the consumption of spare parts separately, the combined prediction model is established by optimizing the combination of these single prediction methods, and the result with the minimum prediction error is taken as the predicted value of consumption. A concrete example shows that the combined prediction model is more accurate and has higher practicability and generalization.

INFORMATION TECHNOLOGIES FOR FORECASTING CAR DEPOT INVENTORY USING CORRELATION ANALYSIS

The analysis of the statistics of expenses of components and spare parts of mobile units of the car depot is carried out, the trend of changes in expenses is determined and the mathematical apparatus for forecasting the need for spare parts is selected, which provides the maximum accuracy of the forecast.Forecasting of changes in the parameters of various systems is performed using information about the factors that affect the predicted parameter, using regression models. A multivariate regression model is proposed that takes into account the factors that affect the consumption of spare parts and establishes the density of the relationship between the factors themselves.

A methodology for evaluating the efficiency of driving a truck

The article considers the issues of evaluating the efficiency of converting thermal energy into mechanical work when operating pit vehicles - BELAZ-7540B dump trucks in mountain conditions and the role of the driving skills in this process. The article also defines the efficiency of driving a vehicle, based on which it presents a methodology and mathematical models for evaluating the driver’s efficiency. At the same time, the basis is formed by several operational indicators, out of which the most important ones for mountain operating conditions of heavy-duty trucks - dump trucks are energy, economic and reliability indicators. The driver’s efficiency is evaluated by the energy and economic indicators based on the trip fuel consumption and the performance of the vehicle - dump truck per shift. The efficiency of driving a heavy-duty truck - a dump truck by the material costs indicator is evaluated by the consumption of spare parts and repair and maintenance materials. The driver’s efficiency is evaluated by the reliability indicators based on the specific time, labor, and money costs spent on eliminating operational and resource failures.